We use the eGeMAPS [1]} feature set
designed to standardize features used in affective computing. The eGeMAPS feature
set contains a total of 88 features, including frequency, energy, spectral, cepstral, and dynamic information. The final feature vectors for each
utterance are obtained by applying the following statistics: mean, coefficient
of variation, 20-th, 50-th, and 80-th percentile, range of 20-th to 80-th
percentile, mean and standard deviation of the slope of rising/falling signal
parts, mean of the Alpha Ratio, the
Hammarberg Index, and the spectral slopes from 0–500Hz and 500–1500Hz.
We perform dataset-specific global \(z\) -normalization on all features.
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